226 algorithm-development-"The-University-of-Edinburgh" Postdoctoral positions in Germany
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Your Job: Design and development of a modular high throughput sample environment for chemical hydrogen storage investigations under realistic conditions Design, optimization, and testing of sample
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interdisciplinary and international team of computational and experimental scientists, gaining unique opportunities to develop novel computational tools and pipelines for the analysis and integration of genomic
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20.09.2025, Wissenschaftliches Personal We are seeking a PhD or Postdoctoral researcher to join the AI in Orthopaedics group (TUM & TUM University Hospital). The position focuses on developing
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on the data recorded in the team, you will develop and test machine learning algorithms for perovskite tandem solar cells' energy yield and degradation Data cleaning and preparation Assisting integration
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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training
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- conducting processors with respect to practical short-depth (NISQ) quantum algorithms Cooperate and actively work with experimental partners developing quantum processors using these technological platforms
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classical topics in numerical analysis, such as the analysis of nonlinear PDEs or the development of new solver- or coupling-methods including their convergence analysis, but also modeling and simulation
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the acceleration of relativistic plasma in jets. Developments of new automated algorithms for VLBI model-fitting, kinematics measurements and robustness assessment. 2. Probing the physical mechanism of neutrino
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Fritz Haber Institute of the Max Planck Society, Berlin | Berlin, Berlin | Germany | about 2 months ago
project within the SusMax network focused on developing interpretable machine-learning frameworks for kinetic multiphase reaction-network discovery in the catalytic conversion of renewable feedstocks
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and